Data detection type across the map: How to choose enabled/valid, active, gender, blue number? ——B2B overseas customer acquisition guide

When acquiring customers overseas, data detection is the core link to improve conversion rates and reduce ineffective delivery. Whether you are doing Telegram private message promotion, WhatsApp community recruitment, or iMessage targeted outreach, only by choosing the right detection type can you spend your budget on real, active, and matching users. This article will break down the meaning and applicable scenarios of detection types such as open/valid, activity, gender recognition, blue number/iMessage, etc., to help you quickly match the optimal screening strategy. At the end of the article are attached precautions for batch operations, welcome to collect them.

What is data detection? Why is it needed when acquiring customers overseas?

Data detection, simply put, is to verify the status of the mobile phone number on the target platform through technical means - is the number registered with Telegram? Have you been active in the last 7 days? Is the user male or female? Do you have an iOS device (blue number)? This information directly determines whether you can effectively reach target users.

In overseas marketing scenarios, untested number lists often contain a large number of “dead numbers” or “fake numbers”. Directly sending private messages in batches not only wastes costs, but may also lead to account closure due to high complaint rate. By pre-screening numbers that are open, active and matching gender through data detection, the effective delivery rate can be increased from 30% to 50% to more than 80%. The following four detection types are currently the most commonly used in B2B customer acquisition.

Detailed explanation of the four core detection types: activated/valid, active, gender, blue number

1. Activation/validity detection - Is the number registered with the target platform?

Meaning: Verify whether the mobile phone number has been registered on the target platform. For example:

• Telegram activation detection: Check whether the number is a registered Telegram user.
• WhatsApp activation detection: Check whether the number has a WhatsApp account.

Typical uses:

• Filter unregistered numbers to avoid sending failed messages (such as WhatsApp prompting “This user is not registered”).
• Reduce the probability of the account triggering risk control due to a large number of invalid sendings.

Applicable Scenarios: Any initial screening step when preparing to send private messages in batches or add friends. It is recommended as the first screen to eliminate unregistered numbers.

2. Activity detection - has the user been online recently?

Meaning: Detect whether the number has logged in within the specified time window. For example:

• Telegram activity detection: You can preset windows such as “Active in the past 7 days” and “Active in the past 30 days”.
• WhatsApp activity detection: Returns the last online time or login days.

Typical uses:

• Lock in real users who have been active recently to avoid sending to abandoned accounts (such as numbers that have not logged in six months after registration).
• Increase message open rates - active users are more likely to view messages or join communities.

Applicable scenarios:

• Community recruitment: Telegram users who have been active in the past 7 days will be invited first.
• Limited time promotion: only sent to WhatsApp users who have logged in within 7 days.

3. Gender identification and age field-accurately target people

Meaning: Infer the gender and approximate age range of number users based on platform public data (such as avatar, nickname, public information). For example:

• Telegram gender detection: returns “male” and “female”.
• Age field: can provide range values ​​such as “about 30 years old” and “about 25 years old” (non-ID card level precise data).

Typical uses:

• Target male/female users to promote specific products (such as women’s skin care products → female users; male fitness supplements → male users).
• Combine the age field to filter out the target age group (for example, people around 30 years old are more suitable for investing in financial products).

Note: The accuracy is affected by the richness of public data and is not 100%, but it has met the rough screening needs of most B2B marketing. Do not use it as legal proof of personal identification.

4. Special detection such as blue account/iMessage - mining high-value users

Meaning:

• Blue Tick: Check whether the number is platform certified or a premium user. For example, iOS device blue number (usually refers to Apple device users).
• iMessage Valid Number Detection: Verify that the number can send messages via iMessage (indicating that the user owns an Apple device).

Typical uses:

• Push services that only iOS users can enjoy (such as in-app purchases, Apple ecological tools).
• Identify users with high consumption potential (Apple device users tend to be more willing to pay).

Applicable scenarios:

• High-priced SaaS tools, paid courses, and digital product promotion.
• It is necessary to ensure that the message is reached through iMessage (to avoid the ordinary SMS interception rate).

How to select the data detection type based on customer acquisition scenarios?

Different customer acquisition goals correspond to different detection combinations. The following are three typical scenarios and recommended configurations:

Private message promotion scenario

• Goal: Send private messages in batches to ensure delivery rate and reduce risk control.
• Recommended Combination: Open Detection + Active Detection.
  • First use activation detection to eliminate unregistered numbers.
  • Then use activity detection (such as active in the past 30 days) to filter abandoned accounts.
• Effect: The sending failure rate can be reduced to less than 5%, while avoiding no feedback after sending.

Social promotion of new scenes

• Goal: Invite users to Telegram groups or WhatsApp broadcasts.
• Recommended combination: Active detection (last 7 days).
  • Active users are more likely to accept group invitations and interact.
• Optional Overlay: If the group theme is obviously male/female, gender detection can be added for targeted invitations (such as male gaming communities).

High customer unit price product targeting

• Goal: Push high-priced services to users who have the ability to pay.
• Recommended Combination: Gender Detection + Blue Number/iMessage Detection.
  • Gender detection locks the target gender.
  • Blue number detection (or iMessage valid detection) identifies Apple device users, who are usually more willing to pay.
• Optional Overlay: The age field narrows the range, such as male users around 30 years old.

What other key matters need to be paid attention to when screening numbers in batches?

• Balance Control: Every time a task is submitted, the platform will first display the estimated cost. Be sure to confirm that the balance is sufficient and the price is reasonable before executing. For detailed unit prices, please check Console Real-time Price.
• Task upper limit: The maximum number of numbers in a single task is about 1 million. Exceeds can be submitted in batches.
• Cross-platform multiple screen numbers: The same number can be submitted for testing on different platforms successively (for example, Telegram is activated first, and then WhatsApp is active), but it is recommended to process it in batches according to the platform to avoid errors due to confusion of results.
• Export fields: After the detection is completed, please compare the CSV/TXT file exported by the console to confirm whether the required fields are complete (such as tgid, wsid, gender, active days, etc.).

How to use data detection and number generation together?

The KK-DATA platform designs number generation and data detection as a complete pipeline:

1. Global number generation (free): Generate random numbers by country/region, number segment, custom CSV, etc. The generation itself does not consume the balance.
2. Data detection (deduction by item): Submit the generated number to the detection module, select “activation + active + gender” and other types, the system will detect each item and output the results.
3. Duplication Export: Test results can be imported into the “Data Deduplication Warehouse” to avoid duplicate fees for subsequent repeated submissions of the same number.

This “generate → detect → export” model is very suitable for teams to mass-produce high-quality customer acquisition lists: first use free generation tools to assemble a pool of numbers, and then only detect the required parts in a pay-per-volume manner, significantly reducing initial investment.

FAQ

**Q: What is the difference between enabled detection and effective detection? ** Answer: The activation test only verifies whether the number has been registered on the platform; effective detection usually includes activation verification + additional status confirmation (for example, the number is not blocked and can receive messages). Different platforms have different definitions of “valid”, and the specific fields are subject to the results exported by the console.

**Q: How accurate is gender detection? ** Answer: Gender detection is based on public data inference on the platform and is not 100% accurate, but it can meet the rough screening needs of most B2B marketing (such as targeting men/women). The age field is a range value (such as “about 30 years old”) and cannot be used as ID-level precise data.

**Q: Can multiple detection types be selected for one screening task at the same time? ** Answer: Yes. When submitting a task, you can check multiple detection types (such as activation + activity + gender), and the system will detect each item one by one and merge the output results. The fees are accumulated based on the unit price of each type. For details, see the real-time price on the console.

**Q: How to export the data after the test is completed? ** Answer: After the task is completed, you can directly download the CSV or TXT format file in the console, including all selected detection fields (such as tgid, gender, age, active days, etc.).

**Q: If the previously screened number is submitted again, will it be deducted again? ** Answer: It is strongly recommended to use the platform’s “Data Deduplication Warehouse” function to import historical numbers. The system will automatically skip the detected numbers to avoid repeated deductions. If you directly resubmit files without deduplication, each task will be billed independently and duplicate charges may be incurred.

---

The above are the four major types of data detection and their practical combination strategies. Choosing the right detection type can maximize your customer acquisition costs. Log in to the console immediately to experience the complete screening function, or contact customer service for one-on-one guidance.

👉Log in to the console to start screening numbers Two-way contact customer service: https://t.me/kkdata_robot Official website to learn about all detection types: https://kkdata.cc/ Usage documentation: https://docs.kkdata.cc/